Summary and Schedule
Epiverse-TRACE tutorials
The Epiverse-TRACE tutorials are training materials for Outbreak Analysis tasks aimed at learners who are willing to achieve basic competence in modelling and analytics.
The tutorials are built around the workflow of outbreak analysis split into three stages : early tasks, middle tasks and late tasks.
Task topics consist of one or more episodes. You can navigate to different episodes using the menu on the left hand side. Alternatively, you may find the topic you are interested in the key points of each episode.
Each episode contains:
- Overview : describes what questions will be answered and what are the objectives of the episode.
- Prerequisites: describes what episodes/packages need to be covered before the current episode.
- Example R code : work through the episodes on your own computer using the example R code.
- Challenges : complete challenges to test your understanding.
- Explainers : add to your understanding of mathematical and modelling concepts with the explainer boxes.
Also check out the glossary for any terms you may be unfamiliar with.
Related projects
- R package vignettes : for R package
{package}
find the vignette located athttps://epiverse-trace.github.io/{package}/
. Look at all Epiverse-TRACE packages in our developer space. - How-to guides : reproducible recipes with concrete steps to solve specific Outbreak Analysis questions.
- The Epidemiologist R Handbook : Quick R code reference manual with task-centered examples that address common epidemiological problems.
- COMING SOON case studies : reproducible case-studies of outbreak data analysis tasks using R packages.
This tutorial was built with The Carpentries Workbench.
Setup Instructions | Download files required for the lesson | |
Duration: 00h 00m | 1. Outbreak analytics pipelines |
Why use R packages for Outbreak analytics? What can we do to analyse our outbreak data? How can I start doing Outbreak Analytics with R? |
Duration: 00h 12m | 2. Read delays |
How to get delay distributions from a systematic review? How to connect reused delays with my existing analysis pipeline? When should delays be reused from a systematic review? |
Duration: 00h 24m | 3. Quantifying transmission |
How can I estimate key transmission metrics from a time series of case
data? How can I quantify geographical heterogeneity in these metrics? |
Duration: 00h 54m | 4. Create a short-term forecast |
How do I create short-term forecasts from case data? How do I account for incomplete reporting in forecasts? |
Duration: 01h 54m | 5. Simulating transmission |
How do I simulate disease spread using a mathematical model? What inputs are needed for a model simulation? How do I account for uncertainty? |
Duration: 03h 09m | 6. Choosing an appropriate model | How do I choose a mathematical model that’s appropriate to complete my analytical task? |
Duration: 03h 39m | 7. Modelling interventions | How do I investigate the effect of interventions on disease trajectories? |
Duration: 04h 54m | 8. Comparing public health outcomes of interventions | How can I quantify the effect of an intervention? |
Duration: 06h 09m | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
Software Setup
Setup instructions live in this document. Please specify the tools
and the data sets the learner needs to have installed. If you want to
hide different setup instructions, you can use a solution
tag.
Install R and RStudio
R and RStudio are two separate pieces of software:
- R is a programming language and software used to run code written in R.
- RStudio is an integrated development environment (IDE) that makes using R easier. In this tutorial, we use RStudio to interact with R.
If you don’t already have R
and RStudio
installed, follow the instructions for your operating system at https://posit.co/download/rstudio-desktop/.
Update R and RStudio
This tutorial requires R version 4.0.0 or later.
If you already have R and RStudio installed, first check if your R version is up to date:
When you open RStudio your R version will be printed in the console on the console window. Alternatively, you can type
sessionInfo()
into the console.If your version of R is older than the one required, download and install the latest version of R from the R project website for your operating system.
After installing a new version of R, you will have to reinstall all your packages with the new version. For Windows, there is a package called
installr
that can help you with upgrading your R version and migrating your package library.To update RStudio to the latest version, open RStudio and click on
Help > Check for Updates
. If a new version is available follow the instructions on the screen. By default, RStudio will also automatically notify you of new versions every once in a while.
Callout
While this may sound scary, it is far more common to run into issues due to using out-of-date versions of R or R packages. Keeping up with the latest versions of R, RStudio, and any packages you regularly use is a good practice.
Install required R packages
During the tutorial, we will need a number of R packages. Packages contain useful R code written by other people. We will use packages from the Epiverse-TRACE.
To try to install these packages, open RStudio and copy and paste the following code chunk into the console window, then press the Enter (Windows and Linux) or Return (MacOS) to execute the command.
R
if(!require("pak")) install.packages("pak")
new_packages <- c(
"EpiNow2",
"epiverse-trace/epiparameter",
"socialmixr",
"epiverse-trace/epidemics",
"tidyverse"
)
pak::pak(new_packages)
You should update all of the packages required for the tutorial, even if you installed them relatively recently. New versions bring improvements and important bug fixes.
When the installation has finished, you can try to load the packages by pasting the following code into the console:
R
library(EpiNow2)
library(epiparameter)
library(socialmixr)
library(epidemics)
library(tidyverse)
If you do NOT see an error like
there is no package called ‘...’
you are good to go! If you
do, contact us!
Data sets
Your Questions
If you need any assistance installing the software or have any other questions about this tutorial, please send an email to andree.valle-campos@lshtm.ac.uk